20 #include <cumlprims/opg/matrix/data.hpp>
21 #include <cumlprims/opg/matrix/part_descriptor.hpp>
22 #include <raft/core/comms.hpp>
24 #include <cuda_runtime.h>
42 Matrix::PartDescriptor& input_desc,
43 std::vector<Matrix::Data<T>*>& labels);
60 void qnFit(raft::handle_t& handle,
61 std::vector<Matrix::Data<T>*>& input_data,
62 Matrix::PartDescriptor& input_desc,
63 std::vector<Matrix::Data<T>*>& labels,
91 template <
typename T,
typename I>
93 std::vector<Matrix::Data<T>*>& input_values,
97 Matrix::PartDescriptor& input_desc,
98 std::vector<Matrix::Data<T>*>& labels,
101 bool standardization,
Definition: kernelparams.h:21
std::vector< T > getUniquelabelsMG(const raft::handle_t &handle, Matrix::PartDescriptor &input_desc, std::vector< Matrix::Data< T > * > &labels)
Calculate unique class labels across multiple GPUs in a multi-node environment.
void qnFitSparse(raft::handle_t &handle, std::vector< Matrix::Data< T > * > &input_values, I *input_cols, I *input_row_ids, I X_nnz, Matrix::PartDescriptor &input_desc, std::vector< Matrix::Data< T > * > &labels, T *coef, const qn_params &pams, bool standardization, int n_classes, T *f, int *num_iters)
support sparse vectors (Compressed Sparse Row format) for MNMG logistic regression fit using quasi ne...
void qnFit(raft::handle_t &handle, std::vector< Matrix::Data< T > * > &input_data, Matrix::PartDescriptor &input_desc, std::vector< Matrix::Data< T > * > &labels, T *coef, const qn_params &pams, bool X_col_major, bool standardization, int n_classes, T *f, int *num_iters)
performs MNMG fit operation for the logistic regression using quasi newton methods
Definition: dbscan.hpp:30